1,721,024 research outputs found
Dataset representativeness during data collection in three UK social surveys: generalizability and the effects of auxiliary covariate choice
No full textData set representativeness during data collection in three UK social surveys: generalizability and the effects of auxiliary covariate choice
Get PDFWe consider the use of representativeness indicators to monitor risks of non‐response bias during survey data collection. The analysis benefits from use of a unique data set linking call record paradata from three UK social surveys to census auxiliary attribute information on sample households. We investigate the utility of census information for this purpose and the performance of representativeness indicators (the R‐indicator and the coefficient of variation of response propensities) in monitoring representativeness over call records. We also investigate the extent and effects of misspecification of auxiliary covariate sets used in indicator computation and design phase capacity points in call records beyond which survey data set improvements are minimal, and whether such points are generalizable across surveys. Given our findings, we then offer guidance to survey practitioners on the use of such methods and implications for optimizing data collection and efficiency savings
Correlates of record linkage and estimating risks of non-linkage biases in business datasets
No full textResearchers often utilise datasets that link information from multiple sources, but non-linkage biases caused by linked and non-linked subject differences are little understood, especially in business datasets. We address these knowledge gaps by studying biases in linkable 2010 UK Small Business Survey datasets. We identify correlates of business linkage propensity, and also for the first time its components: consent to linkage and register identifier appendability. As well, we take a novel approach to evaluating non-linkage bias risks, by computing dataset representativeness indicators (comparable, decomposable sample-subset similarity measures). We find that the main impacts on linkage propensities and bias risks are due to consenter / non-consenter differences explicable given business survey response processes, and differences between subjects with and without identifiers caused by register under-coverage of very small businesses. We then discuss consequences for the analysis of linked business datasets, and implications of the evaluation methods we introduce for linked dataset producers and users
Fieldwork effort, response rate, and the distribution of survey outcomes: a multi-level meta-analysis
Get PDFWe assess how survey outcome distributions change over repeated calls made to addresses in face-to- face household interview surveys. We consider this question for 559 survey variables, drawn from six major face-to-face UK surveys which have different sample designs, cover different topic areas, and achieve response rates between 54% and 76%. Using a multi-level meta-analytic framework, we estimate for each survey variable, the expected difference between the point estimate for a proportion at call n and for the full achieved sample. We find that most variables are surprisingly close to the final achieved sample distribution after only one or two call attempts and before any post- stratification weighting has been applied; the mean expected difference from the final sample proportion across all 559 variables after 1 call is 1.6%, dropping to 0.7% after 3 calls, and to 0.4% after 5 calls. These estimates vary only marginally across the six surveys and the different types of questions examined. Our findings add further weight to the body of evidence which questions the strength of the relationship between response rate and nonresponse bias. In practical terms, our results suggest that making large numbers of calls at sampled addresses and converting ‘soft’ refusals into interviews are not cost-effective means of minimizing survey error
Do coefficients of variation of response propensities approximate non-response biases during survey data collection?
Get PDFWe evaluate the utility of coefficients of variation of response propensities (CVs) as measures of risks of survey variable non-response biases when monitoring survey data collection. CVs quantify variation in sample response propensities estimated given a set of auxiliary attribute covariates observed for all subjects. If auxiliary covariates and survey variables are correlated, low levels of propensity variation imply low bias risk. CVs can also be decomposed to measure associations between auxiliary covariates and propensity variation, informing collection method modifications and post-collection adjustments to improve dataset quality. Practitioners are interested in such approaches to managing bias risks, but risk indicator performance has received little attention. We describe relationships between CVs and expected biases and how they inform quality improvements during and post-data collection, expanding on previous work. Next, given auxiliary information from the concurrent 2011 UK census and details of interview attempts, we use CVs to quantify the representativeness of the UK Labour Force Survey dataset during data collection. Following this, we use survey data to evaluate inference based on CVs concerning survey variables with analogues measuring the same quantities among the auxiliary covariate set. Given our findings, we then offer advice on using CVs to monitor survey data collection.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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